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My research @ MobiSys   (daniele quercia) U   C   L
I research @ ...
U niversity C ollege L ondon
I’m part of ...
MobiSys
<MobiSys>
We   research  distributed systems (mostly mobile)
We   blog mobblog ucl
We?  2 examples...
How to make it distributed. Traditional Collaborative Filtering: centralized
h How to make it  distributed (neal lathia)
temporal evolution of ratings 1. Temporal Evolution of Ratings
2. Trustworthiness of ratings
Computing on Sensors: Limited  &  Oversimplified
Computing on Sensors: Limited  &  Oversimplified Sensors form a ...
Ways of  sharing load (elisa rondini)
Two ways already work ...
on a large  testbed !
</MobiSys>
<My Research>
Reputation Systems for Mobiles
Daniele Quercia Situation : People exchange   digital content
Problem : content overload content drowning user help! who will come to the rescue?
Proposal:   Accept content only   from  reputable  people
Who is   reputable ? That’s subjective!
Daniele Quercia Take two devices… A B
Daniele Quercia A B Shall I accept  content from  B ?
Daniele Quercia A B A  should  set  its trust  for  B
Daniele Quercia A B A  should  set  its trust  for  B Yes, but how? That’s my research!
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Mobisys

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Transcript of "Mobisys"

  1. 1. My research @ MobiSys (daniele quercia) U C L
  2. 2. I research @ ...
  3. 3. U niversity C ollege L ondon
  4. 4. I’m part of ...
  5. 5. MobiSys
  6. 6. <MobiSys>
  7. 7. We research distributed systems (mostly mobile)
  8. 8. We blog mobblog ucl
  9. 9. We? 2 examples...
  10. 10. How to make it distributed. Traditional Collaborative Filtering: centralized
  11. 11. h How to make it distributed (neal lathia)
  12. 12. temporal evolution of ratings 1. Temporal Evolution of Ratings
  13. 13. 2. Trustworthiness of ratings
  14. 14. Computing on Sensors: Limited & Oversimplified
  15. 15. Computing on Sensors: Limited & Oversimplified Sensors form a ...
  16. 16. Ways of sharing load (elisa rondini)
  17. 17. Two ways already work ...
  18. 18. on a large testbed !
  19. 19. </MobiSys>
  20. 20. <My Research>
  21. 21. Reputation Systems for Mobiles
  22. 22. Daniele Quercia Situation : People exchange digital content
  23. 23. Problem : content overload content drowning user help! who will come to the rescue?
  24. 24. Proposal: Accept content only from reputable people
  25. 25. Who is reputable ? That’s subjective!
  26. 26. Daniele Quercia Take two devices… A B
  27. 27. Daniele Quercia A B Shall I accept content from B ?
  28. 28. Daniele Quercia A B A should set its trust for B
  29. 29. Daniele Quercia A B A should set its trust for B Yes, but how? That’s my research!
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